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Tackling unresolved questions in forest ecology: The past and future role of simulation models.

Authors :
Maréchaux I
Langerwisch F
Huth A
Bugmann H
Morin X
Reyer CPO
Seidl R
Collalti A
Dantas de Paula M
Fischer R
Gutsch M
Lexer MJ
Lischke H
Rammig A
Rödig E
Sakschewski B
Taubert F
Thonicke K
Vacchiano G
Bohn FJ
Source :
Ecology and evolution [Ecol Evol] 2021 Mar 30; Vol. 11 (9), pp. 3746-3770. Date of Electronic Publication: 2021 Mar 30 (Print Publication: 2021).
Publication Year :
2021

Abstract

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.<br />Competing Interests: The authors state that there is no conflict of interest.<br /> (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
2045-7758
Volume :
11
Issue :
9
Database :
MEDLINE
Journal :
Ecology and evolution
Publication Type :
Academic Journal
Accession number :
33976773
Full Text :
https://doi.org/10.1002/ece3.7391